Adaptive design for identifying maximum tolerated dose early to accelerate dose-finding trial

Abstract

Purpose The early identification of maximum tolerated dose (MTD) in phase I trial leads to faster progression to a phase II trial or an expansion cohort to confirm efficacy. Methods We propose a novel adaptive design for identifying MTD early to accelerate dose-finding trials. The early identification of MTD is determined adaptively by dose-retainment probability using a trial data via Bayesian analysis. We applied the early identification design to an actual trial. A simulation study evaluates the performance of the early identification design. Results In the actual study, we confirmed the MTD could be early identified and the study period was shortened. In the simulation study, the percentage of the correct MTD selection in the early identification Keyboard and early identification Bayesian optimal interval (BOIN) designs was almost same from the non-early identification version. The early identification Keyboard and BOIN designs reduced the study duration by about 50% from the model-assisted designs. In addition, the early identification Keyboard and BOIN designs reduced the study duration by about 20% from time-to-event model-assisted designs. Conclusion We proposed the early identification of MTD maintaining the accuracy to be able to short the study period.

In Vitro and In Vivo Evaluation of Lactoferrin-Modified Liposomal Etomidate with Enhanced Brain-Targeting Effect for General Anesthesia

“…This result was near our previously reported LD 50 values of an etomidate-encapsulated micelle and the commercial etomidate emulsion (i.e., about 20 mg etomidate/kg), indicating the safety of the liposomal etomidate [ 8 ]. The MTD value was investigated as an indicator to determine the safe dose range for a single intravenous injection [ 55 ]. Four different dose levels (i.e., 12, 14, 16, and 18 mg etomidate/kg) near the LD 50 values of the liposomal etomidate were tested in this experiment.…”

Nature-Derived Compounds as Potential Bioactive Leads against CDK9-Induced Cancer: Computational and Network Pharmacology Approaches

“…Even when treating acute and more severe diseases, doctors frequently exceed the maximum tolerated dosage (MTD) despite the lack of evidence that doing so is more likely to enhance patient outcomes [152,153]. Cardiovascular guidelines advise MTD even in prevention without clear evidence of improved outcomes for several indications, such as hypercholesterolemia [153][154][155]. The MTD values for LCI, geniposidic acid, quercetin, geniposide, curcumin, and withanolide C estimated as 0.142, 1.339, 0.499, 0.528, 0.081, and −0.694.…”

Data-dependent early completion of dose-finding trials for drug-combination

“…Although the BOIN and Keyboard designs have a stopping rule that can be used to terminate the trial if the number of patients treated exceeds the predetermined number, there is no statistical basis for the predetermined number. Kojima [35][36][37] proposed an early completion method for model-assisted designs but did not discuss the applicability of this method for dose combination trials.…”

“…[2][3][4][5][6][7][8][9][10][11][12][13][14][15] However, such model-based designs are rarely used in actual clinical trials because they require complex assumptions to be made. 16 Therefore, Bayesian optimal interval (BOIN), [19][20] Keyboard, 21 modified toxicity probability interval (mTPI), 17 mTPI-2, 18 and extended model-assisted designs [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] have been proposed as simple models that perform well in selecting MTDs. Pan et al (2020) 23 have extended the Keyboard design to the drug-combination dose-finding design.…”